Bayesian Analysis of Hierarchical Models and its Application in Agriculture
by Nageena nazir, Athar Ali Khan, Sameera Shafi and Anjum Rashid.
The Hierarchical model has been discussed and implemented from Bayesian viewpoint. The mixed effects models lack statistical and philosophical grounds and Bayesian approach is the only remedy for such models. Bayesian statistics is an excellent alternative to be more reasonable for moderate and especially for small sample sizes when non Bayesian procedures do not work (e.g., Berger 1985, page 125). In this paper we have made Bayesian analysis of Hierarchical Models and illustrated its application in agriculture. Advancement in the computational power of high speed computers has aided the application part. Suitable illustrations have been proposed on real data set generated on potato crop in year 2005-2006 at five different locations with twelve genotypes in SKUAST-(K).
Bayesian Analysis, Bayesian Statistics, Hierarchical Model
Nageena Nazir, firstname.lastname@example.org
Athar Ali Khan,
Anjum Rashid. Anjum Rashid
READING THE ARTICLE: You can read the article in
portable document (.pdf) format (84309 bytes.)
NOTE: The content of this article is the intellectual property of the authors, who retains all rights to future publication.
This page has been accessed 2559 times since APRIL 21, 2009.
Return to the Home Page.